This project examines how the current changes in the political information environments in European democracies affect the conditions for a healthy democracy. As a theoretical background we employ the concept of ‘political information environment’ (PIE) that includes both the supply and demand of political news and information. Supply refers to the quantity and quality of news and public affairs content provided through traditional and new media sources, demand captures the amount and type of news and information the public wants or consumes. Recent changes in the political information environment may lead to a growing number of uniformed, misinformed and selectively informed citizens, potentially endangering the functioning of democracy. To examine these concerns, the study aims at investigating the following: (1) how do citizens today gain political information and how does this relate to their political attitudes and behaviour; (2) what is the content and quality of the information citizens are exposed to; (3) where do divides between being informed and not being informed exist, across and within European societies, and (4) how can citizens be empowered to navigate and find valuable information. We will do this through a series of comparative, innovatively designed studies, including web tracking, comparative surveys, focus groups and survey-embedded experiments in 14 European countries and the US. These countries vary on a number of key contextual factors relevant for the study, covering both “young” and established democracies with different democratic traditions, media systems, and news consumption habits.

The proposed project aims to improve the process of collecting, categorising, and analysing historical occupational data, as well as making it possible to integrate existing historical occupational data with modern classification systems. Digital data on occupations are only available for the period covering last four to five decades. Without data that covers longer periods, it is impossible to understand the impact of long-term social and economic processes such as industrialisation, slow-evolving environmental factors, or, conversely, infrequent events like pandemics, sudden economic shocks or policy changes by comparing them to other economies or previous occurrences. This project aims to fill this gap in the data landscape by focusing on data from over 20 countries spanning multiple centuries. We plan to develop a revised coding scheme that is specially designed to make historical occupational data compatible with 16 globally accepted occupational and industrial coding schemes to offer the most comprehensive view of employment trends over time. The project is based on the world's largest dataset of historical occupational data created by the Cambridge Group for the History of Population and Social Structure (CAMPOP) and affiliated international research groups over several decades. To promote the use of this extensive dataset, a web-based tool was created for data conversion between the various coding schemes. Building on this, we will incorporate machine learning algorithms to permit the rapid and precise labelling of historical occupations through our interface. The data will be publicly available, enabling a wide range of applications, including innovative visualisation and analysis. Moreover, the project extends the EU ESCO coding scheme to include historical occupational data from 28 languages. We will also develop multilingual occupational descriptors (a textual description of what each occupation consisted of) that will allow us and others to understand changes in the nature of work much more precisely. The tool, data, methodology, and outreach material created will benefit a broad range of researchers in social sciences, educators at the secondary and tertiary levels, data-driven policymakers, and the general public. The project is backed by an experienced team at CAMPOP, and will be developed in collaboration with the European Commission, the Warwick Institute for Employment Research, and the University of Southern Denmark.

Currently medicine tends to treat distinct diseases individually. We are increasingly aware that people do not suffer from one disease in isolation. Current treatment means that many people are taking multiple medications, which increases side-effects and can lead to harmful drug interactions. We now know that groups of diseases tend to cluster together, such that an individual with one disease is more likely to have others in the cluster. We think this is because there are underlying mechanisms which are root causes of many diseases at the same time. Age is the major risk factor for getting many diseases. Biologists have studied ageing in model organisms and humans for many years. This body of work is called Geroscience. Geroscience has now identified key mechanisms which occur in ageing and contribute to changes in physiology and health. We want to investigate how these processes relate to the development of disease clusters. By understanding the mechanisms behind the development of these disease clusters we aim to develop strategies to combat the root causes, thereby preventing or treating multiple diseases at once. Geroscience has identified three key changes which occur with ageing and contribute to health problems: cell senescence (where old cells do not die but remain in tissues secreting molecules which upset healthy cells); changes in nutrient sensing (where the cell system inappropropriately assesses the balance between growth and health), and altered autophagy (problems recycling proteins in the cells such that they accumulate and affect cell function). All three of these mechanisms have possible therapies which could be used to stop the underying process. Importantly, some of these therapies are drugs like metformin or lifestyle changes such as diet alterations which are already used in humans and known to be relatively safe. Our consortium contains internationally recognised expertise across five universities with experts from discovery science, ageing biology, computational biology, clinical trial design, and medicine who will work together to develop a new strategy for treatment. Our vision is to bring a paradigm shift in the clinical management of age-related multimorbidity, via modulation of the upstream drivers of the major disease clusters, replacing the current approach of treating diseases separately. The overarching aim of our proposal is to build a multidisciplinary collaborative to identify whether these ageing mechanisms underpin the development of distinct multimorbidity clusters. The consortium is led by doctors and will involve clinical trial experts to keep us focused on developing new treatment strategies quickly. Our plan is to use data from large cohorts which already have many biological and health measures characterised, to investigate the biology behind multimorbidity clusters. We will start with the TwinsUK cohort which has had molecular biology assayed in detail, from genes, to expression of genes, proteins, metabolites and cell subsets. In the first six-month consolidation phase, we will construct the clusters in this dataset and look at the relationships between biology and the clusters. We will also extend the team to involve additional scientific experts. In the consortium phase we will extend this to other cohorts and perform experiments on cells derived from participants and then in clinical studies to demonstrate cause and effect, and investigate how we can modify and treat multiple diseases safely (Figure 1). Combining this understanding with our collaborative's expertise in novel clinical trial designs, we will develop protocols for testing treatments targeting the identified mechanisms in people suffering from multiple diseases.

The element nitrogen (N) is key to life - building proteins and the very DNA that tells life what to do. Nitrogen exists largely as di-nitrogen gas (N2) in the atmosphere, with a fraction being present in the organic N of life (humans, animals, plants, microbes etc.). Following death and decay, organic N decomposes to ammonia. The N in ammonia is then cycled back to the atmosphere through a coupling between microbes (microscopic organisms known as bacteria and archaea) that, on the one-hand, use oxygen to convert ammonia into nitrates and, on the other, microbes that respire nitrate in the absence of oxygen back to N2 gas. Oxygen rich, oxic-habitats are all around us, be it agricultural, grassland or forest soils or, indeed, your own back garden. If those soils become water logged, they will lose their oxygen and become anoxic-habitats and the same holds true for muddy sediments at the bottom of seas and lakes - and microbes in those anoxic habitats respire nitrates to N2 gas. This is the N cycle taught at school and although it has been updated in the past 20 years to include novel microbial pathways of producing N2 gas - the coupling between ammonia and N2 gas mediated through nitrates sits at its very heart. What's new? In 2016, Trimmer and his grouped published a paper showing that the division between the recognised oxic and anoxic parts of the N cycle was blurred, with ammonia being converted to N2 gas in clean, oxygen-rich gravel riverbeds. Subsequently, Trimmer had a PhD student continue to explore the N cycle in oxygen-rich gravel riverbeds. The opportunity now for a new international collaboration arouse fortuitously during the examination that PhD student by the external examiner Prof. Bo Thamdrup (University of Southern Denmark) who identified a mistake in an equation in Liao's thesis. Correcting this seemingly innocuous mistake turned out to have profound implications for our understanding of the N cycle; though not only in oxic riverbeds but in many other habitats that drive the Earth's N cycle. What has changed? Correcting the equation led to a new mathematical framework and placing our data into that new framework showed that the patterns in the N2 gas data - in the PhD thesis - disagreed with those expected for a coupling between distinct oxic and anoxic steps in the N cycle. Where that well-recognised coupling should include nitrates, our new mathematical framework argues for a cryptic-coupling that does not involve nitrates. Why does this matter? A cryptic-coupling not only changes our view of a fundamental step in the N cycle but - being hidden - a cryptic-coupling undoes 20 years' of research into the different microbial pathways that make N2 gas and our overall understanding of the N cycle is now challenged. Our new framework suggests a new pathway or at least a new type of coupling between known pathways in the N cycle that needs to be characterised before we can understand the cycling of a key bio-element on Earth. Further, unravelling this cryptic-coupling could facilitate the development of more efficient waste-water treatment i.e., by removing the need for separate oxic and anoxic treatment processes. We cannot, however, probe this new cryptic-coupling in the N cycle using current and widely available techniques - as they are simply blind to what it is we need to study. Hence, now in a new international collaboration we will pioneer the development of new tools to probe a cryptic-coupling in the N cycle. We will share complimentary mass-spectrometer facilities, along with contrasting field-sites and novel isotope and molecular techniques to deliver new fundamental and applied knowledge about the all too common, yet still enigmatic cycling of N on Earth.

In magnetic resonance spectroscopy, the structure and dynamics of molecules and materials is analyzed via the magnetic moment associated with the spin of unpaired electrons and certain nuclei. Information about a sample and its environment can be obtained from coupling constants and coherent interactions that are responsible for the line positions and patterns in a spectrum, and from relaxation transients or linewidths caused by incoherent random processes that lead to a thermal equilibration following an external excitation. In electron paramagnetic resonance (EPR) spectroscopy, which is a technique to study electron spins, samples are very often either polycrystalline or glassy solids. Because various interactions are orientation dependent, so are the relaxation times. Thus relaxation cannot be modelled accurately using a mono-exponential decay function. In order to use relaxation times for characterizing the dynamics of a sample and its interactions with the environment, it is necessary to measure relaxation transiently. Pulse EPR techniques are very powerful in studying samples with slow relaxation. However, for most metal ion compounds, which make for a large fraction of paramagnetic samples, fast transverse relaxation prevents the formation of an echo. These samples can only be studied at cryogenic temperatures, causing the temperature dependence of relaxation times to be available only over a limited temperature range. For longitudinal detection (LOD) of EPR, a coil with its axis parallel to the external magnetic field is used to measure changes of the longitudinal spin magnetization. Such a coil does not pick up a signal from the oscillating magnetic field perpendicular to the external field that is used to excite the electron spins. Therefore it is possible to monitor changes of the longitudinal magnetization even while the sample is irradiated. In this project, a LOD EPR probe optimized for measuring fast longitudinal relaxation transients is being built. By carefully characterizing the transfer function of the probe, the signal can be inverted to obtain the magnetization transient that was inducing the signal. It then becomes possible to measure full longitudinal relaxation transients in a single repetition of an experiment instead of the point-by-point acquisition common in pulse EPR. This facilitates novel multi-dimensional experiments, where relaxation times are correlated with, for example, the resonance frequency. To take full advantage of the available data, analysis routines must be produced to obtain relaxation time distributions. In a next step, experiments will be developed to study interactions between paramagnetic and ordered magnetic domains in paramagnetically doped materials. In transition metal jarosites, the magnetic ordering can be varied between ferromagnetic, antiferromagnetic and frustrated antiferromagnetic, depending on the metal cation. We will study these materials by using a novel experiment to correlate longitudinal relaxation, following a microwave saturation pulse, and the response to a field jump in a minor loop experiment. This type of experiment, in combination with traditional EPR experiments, will allow us to identify the magnetic phases that interact with the microwave field. Eventually we will study interactions between different magnetic phases, which are expected to coexist especially in the temperature range close to a magnetic phase transition.